MIT Department of Aeronautics and Astronautics

HUMAN SYSTEMS ENGINEERING

16.400/16.453

Fall 2022

Lectures Tuesday and Thursday 9:30-11am, 3-370

 

Prof. Katya Arquilla                   Prof. Lonnie Petersen

Pronouns: she/her           Pronouns: she/her

Office: 33-307                          Office: 33-311

arquilla@mit.edu             lgpeters@mit.edu

Office hours: 33-307                 Office hours: 33-311

Tuesdays, 11am-12pm              Thursdays, 11am-12pm

 

This course is designed to provide both undergraduate and graduate students with a fundamental understanding of human factors that must be taken into account in the design and engineering of complex aviation, space, and biomedical systems.  The primary focus is the derivation of human engineering design criteria from an understanding of the information perception and processing capabilities of the human and the most appropriate methods for sharing information between a system and the human.  Students will learn about the sensory, motor, and cognitive resources of the human; principles of information displays and sensory feedback; human-computer interaction and the growing role of automation; and the fundamentals of experimentation with human participants and statistical methods for data analysis. 

By the end of this course, all students will understand the fundamental challenges of designing systems with humans in the loop, be able to ask relevant research questions in the area of human systems engineering, formulate hypotheses, plan experiments to investigate those hypotheses, and analyze experimental results. 

Active learning is an important practice for information processing, so all students are expected to engage in activities and discussion during class.  Lectures will be both in-person and streamed synchronously for students who may be at higher risk from contracting covid-19 to participate remotely.  Remote participants are expected to participate actively in the course.  This is a challenging instructional format, but we will do our best to include both in-person and remote participants, and we are open to feedback on how to improve the educational experience. 

Learning objectives: Given a complex system requiring human interaction, students will be proficient in identifying sensory, motor, and cognitive concerns for expected operational envelopes, developing research questions and hypotheses to evaluate and improve human interaction in these complex systems, generating experimental approaches to effectively investigate hypotheses, analyzing experimental results, and effectively communicating these results through written and oral presentation. 

The course is divided into four educational modules in the following four areas:

MODULE 1 – THE HUMAN AS A SYSTEM

• Sensory systems: visual, auditory, vestibular
• Cognition, decision-making, learning
• The unique challenges of air and space flight; human physiology and medical capabilities

MODULE 2 – FUNDAMENTALS OF DESIGNING AEROSPACE SYSTEMS FOR HUMANS

• Human-computer interaction: Displays, Autonomy
• Hardware-human interaction: Habitat design

MODULE 3: UNDERSTANDING THE HUMAN SYSTEM THROUGH EXPERIMENTATION

• Research questions and hypotheses
• Ethics of experimentation with human participants
• Statistical methods

MODULE 4: IMPLEMENTING HUMAN SYSTEMS ENGINEERING PRINCIPLES

• Socially conscious human systems engineering practices
• Applying human factors principles, experimental design, and statistical methods principles
• Presenting experimental results and providing constructive feedback

 

Assignments and grading

Undergraduate students will demonstrate proficiency through homework assignments, quizzes, and active participation in in-class activities.  Graduate students will complete all the undergraduate requirements, as well as a research-oriented project with a final written report and an oral presentation.  There will be 5 homework assignments throughout the semester, 2 quizzes, and 2 assignments before the final project write-up and presentation to ensure steady progress throughout the semester.  Undergraduate student grades will be 40% homework assignments, 30% quiz 1, and 30% quiz 2.  Graduate student grades will be 25% homework assignments, 25% quiz 1, 25% quiz 2, and 25% project. 

 

COVID-19/sickness policies

Our course will follow the most up-to-date guidance from the Institute for how to maneuver when any one of us contracts covid-19.  If you test positive, please do not come to lecture, but participate in the synchronous lectures remotely.  If one of the instructors tests positive, we will pivot to remote lecturing during the period of quarantine.  If you are symptomatic and feeling unwell (with covid or any other illness), do not attend lecture, get some rest, and let us know how best to support you.  Extensions for assignments can be granted on a case-by-case basis, but we must hear from you before the assignment is due.  

 

Academic Integrity

In this course, we will hold you to the high standard of academic integrity expected of all students at the Institute.  We do this for two reasons.  First, it is essential to the learning process that you are the one doing the work.  We have structured the assignments in this course to enable you to gain deep understanding of the course material.  Failing to do the work yourself will result in a lesser understanding of the content, and therefore a less meaningful education for you.  Second, it is important that there be a level playing field for all students in this course and at the Institute so that the rigor and integrity of the Institute’s educational program are maintained. 

 

Violating the Academic Integrity policy in any way (e.g., plagiarism, unauthorized collaboration, cheating, etc.) will result in official Institute sanction.  Possible sanctions include receiving a failing grade on the assignment or exam, being assigned a failing grade in the course, having a formal notation of disciplinary action placed on your MIT record, suspension from the Institute, and expulsion from the Institute for very serious cases.

 

Please review the Academic Integrity policy and related resources (e.g., working under pressure; how to paraphrase, summarize, and quote; etc.) and contact us if you have any questions about appropriate citation methods, the degree of collaboration that is permitted, or anything else related to the Academic Integrity of this course.

 

Learning accommodations

If you need disability-related accommodation, we encourage you to meet with us early in the semester.  If you have not yet been approved for accommodations, please contact Student Disability Services at sds-all@mit.edu.

 

We look forward to working with you to assist you with your approved accommodations.

 

Student mental health

As a student, you may experience a range of challenges that can interfere with learning, such as strained relationship, increased anxiety, substance use, feeling down, difficulty concentrating and/or lack of motivation.  These mental health concerns or stressful events may impact your ability to attend class, concentrate, complete work, take an exam, or participate in daily activities. 

 

Undergraduate students: Please reach out to Student Support Services (S³).  You may consult with Student Support Services in 5-104 or at (617) 253-4861.

 

Graduate students: Please reach out to the deans for personal support in the Office of Graduate Education.  We recommend reaching out to Suraiya Baluch, Elizabeth Buttenberg, Gaurav Jashnani, and/or Beth A Marois (contact information is on this page: https://officesdirectory.mit.edu/graduate-education).

 

Diversity

MIT values an inclusive environment.  We hope to foster a sense of community in this classroom and consider this classroom to be a place where you will be treated with respect.  We welcome individuals of all backgrounds, beliefs, ethnicities, national origins, gender identities, sexual orientations, religious and political affiliations—and other visible and nonvisible differences.  All members of this class are expected to contribute to a respectful, welcoming, and inclusive environment for every other member of the class.  If this standard is not being upheld, please feel free to speak with us. 

 

Required course text:

• Proctor, R. W., & Van Zandt, T. (2008) Human Factors in Simple and Complex Systems, 2^nd, Boca Raton: CRC Press. (PV)
• Additional required material, including chapters from other texts and journal articles, will be posted to Canvas.

 

Outline of lecture topics (some of the dates and lecture topics here may change, but the assignment dates will not change without at least a week of warning)

Date	Lect	Topic	Reading	Assignments
Sep. 8	1	Introduction	PV, Ch. 1
Sep. 13	2	M1: Sensory systems	PV, Ch. 5, Ch. 7
Sep. 15	3	M1: Sensory systems	PV, Ch. 6, Ch. 8	Problem set 1 assigned   Form graduate student teams
Sep. 20	4	M1: Unique challenges of air and space: Environmental challenges of missions	Barrat: Ch 1
Sep. 22	5	M1: Unique challenges of air and space: Human physiology, cardiovascular and cerebral	Buckey, Ch. 6, 7 Lawley et al., 2017 DVT_NJEM_2020
Sep. 27	6	M1: Attention, workload, situation awareness	PV, Ch. 9,
Sep. 29	7	M1: Memory, information processing, methods of measurement	PV, Ch. 4, Ch. 10	Problem set 1 due
Oct. 4	8	M1: Unique challenges of air and space: Human physiology, Muscle and bone	Buckey, Ch. 1, 4, 8	Problem set 2 assigned
Oct. 6	9	M1: Unique challenges of air and space: Countermeasure and medical capabilities	Buckey Ch 2 Patel et al., 2019
Oct. 11	10	NO CLASS; STUDENT HOLIDAY
Oct. 13	11	M2: Decision-making, human-automation teaming, autonomy	An Introduction to Human Factors Engineering (pdf on Canvas) Chapter 16: Automation & Parasuraman et al., 2000	Graduate student project proposals due
Oct. 18	12	M2: Human-hardware Interaction & habitat Design: Physiological Countermeasures to optimize performance		Problem set 2 due
Oct. 20	13	M2: Human-hardware Interaction & habitat Design: Psychological Countermeasures to optimize performance	Buckey Ch2 and 8
Oct. 25		M2: Light and architecture as a countermeasure (guest lecture)	PV: Ch 18	Problem set 3 assigned
Oct. 27	14	M2: Human-Computer Interaction & Human-Centered Design	Carroll 1997	Problem set 3 assigned
Nov. 1	15	QUIZ 1
Nov. 3	16	M3: Ethics of experimentation	All students complete CITI training
Nov. 8	17	M4: GUEST LECTURE: Human factors research in space analog environments	PV, Ch. 2
Nov. 10	18	M3: Research questions and hypotheses	TBD	Problem set 3 due
Nov. 15	19	M3: Experimental Design	PV, Ch. 2	Problem set 4 assigned
Nov. 17	20	M3: Experimental statistics I	TBD
Nov. 22	21	M3: Experimental statistics II	PV, Ch. 2	Problem set 4 due Problem set 5 assigned
Nov. 24		THANKSGIVING
Nov. 29		M3: Experimental statistics III
Dec. 1	23	Guest lecture: taking a project from research question to experimentation to analysis
Dec. 6		QUIZ 2	Attendance mandatory for all students
Dec. 8	24	Grad student presentations	Attendance mandatory for all students	Problem set 5 due
Dec. 13	25	Grad student presentations	Attendance mandatory for all students	Grad student final written projects due